Essay On HR Statistical Technique

Introduction

In strategic human resource management, HR planning is a very critical component (Watson, 2010). The latter links the former to the organization’s strategic plan. Such a plan serves as a guide towards the achievement of an organizational mission, goals, and objectives. In the modern day business that is characterized by cut-throat competition, HR planning is increasingly becoming a crucial process in a company. It is not enough to recruit the required number of staff to carry out the laid tasks and take up specified corporate responsibilities. It is also of great essence to carry out a comprehensive HR assessment to ensure that the current employees and the ones joining the company have the necessary expertise in line with their respective roles. Additionally, it is significant to ascertain that these employees are flexible to the changes in the industry. Further, such an assessment is also significant in guiding the training and re-training of staff.
As the new HR Director of Ayles Network, I intend to use five HR statistical techniques to assess the staffing, training, and HR assessment that the company currently has in place. These techniques include T-test, ANOVA, Regression Analysis, Trend Analysis, and Supply Forecasting.

Data

For effective analysis, I require the following data:
The years the company recorded the highest and the lowest sales volume and profits.
The number of workforce in each respective year.
The education level and training of employees in those years.
The education level and training of the current workforce.
Effectiveness
Staffing
The regression analysis can be used to assess the effectiveness of the current staffing through analyzing of the past business trends.

Training

Similarly, the training of the current employees can be compared to the level of training in a past workforce that recorded a high performance through the same technique.

HR assessment

Lastly, the regression analysis can be used to assess the current workforce by comparing it to a past date workforce.
The T-test and ANOVA statistical technique can be used to test the impact of either of the two or all three respectively on the human resource performance.

Application

Regression Analysis
Regression Analysis is the most popular statistical technique (Watson, 2010). In this technique, the demand of human resources in the future is determined on the basis of past business factors' trend. These business factors could be sales volume, revenue or profit. Analysts, then determines the relationship between these factors and the number of employees. For instance, if, in 2012, a company recorded $1 million in sales with a workforce of a hundred and fifty, it needs to increase its employees at the present to realize such a feat.
This is achieved through mathematical software, through which experts create a diagram that illustrates the relationship between the highlighted business factor and the number of staffs. The software then calculates a line of regression, which runs through the middle points on the diagram. Observing values at the line helps to determine the workforce required for each value of the considered business factor. Therefore, coming up with such a diagram will help our company in establishing whether the three thousand employees in Ayles Network are adequate to realize the company’s business targets.

T-Test

There is still another commonly used statistical technique referred to as the T-test. There are different varieties of T-test, but the most popular is the 2-sample test also called the independent samples t-test or the student’s t-test (Williamson, 2013). It simply examines the impact of two different independent variables on the mean value of a particular measure. For instance, in our case we might try to find out the impact of staffing and training on the company's objectives. In such a case, we give a questionnaire that attempts independently to measure the impact of staffing and training on company’s performance. The test starts with a null hypothesis, which assumes that there is no difference between the two variables in their regard to their respective impacts on the performance. After gathering data that show a difference in average scores the null hypothesis is rejected.

ANOVA (Analysis of Variance)

Like the above technique, Analysis of Variance assists in testing the impact of independent variables on a particular measure. However, unlike the T-test, which measures two variables, ANOVA tests three or more. There are various varieties of ANOVA like the one-way ANOVA and the two- way ANOVA (Breaugh, 2009). The former is used when the analysis involves at least three independent variables. For instance, in our case, the dependent variable is the human resource performance. Conversely, the independent variables are staffing, HR assessment, and training. The null hypothesis, in this case, is that the mean of the human resource performance is the same in all these independent variables. On the other hand, the alternative is that there is a difference in mean in regard to each variable. The procedure produces an F-statistic that is used in calculating the mean value. Disputing the null hypothesis means that at least two independent variables have a different impact on the dependent variable (Williamson, 2013).

Other Statistical Techniques

There are others statistical techniques that can be used in staffing, training, and HR assessment including Trend Analysis and Supply Forecasting

Trend Analysis

Trend analysis functions best in already existing business as it uses historical staffing data to make future human resources predictions (Breaugh, 2009). It entails creating a relationship between the past and the future business needs, which is achieved through linking the two through a financial or performance metric known as an operational index. For example, we can make an analysis of the current status of staffing in our company, by establishing the number of customers each employee has handled effectively in the past. In addition, we can identify the adequate workforce through finding out the number of employees that produced optimum results in the same period.

Supply Forecasting

It is a statistical technique, which uses replacement charts in establishing employees who are not only available but also qualified to fill demand forecast. The charts include both a diagram and information of an employee current performance, education level, and a flexibility assessment.

Conclusion

The significance of human resource planning and management cannot be overstated in the modern day business. Researchers have identified various techniques that can assist in the entire process. There are different statistical techniques that can be used in assessing the effectiveness of staffing, training HR assessment in an organization. As the new HR Director of Ayles Network, I have identified five techniques, namely T-test, ANOVA, Regression Analysis, Trend Analysis, and Supply Forecasting to aid in this important process.

References

Breaugh, Jack A. (2009). Recruitment and attracting talents: a guide to understanding and managing the recruitment processes. Alexandria, VA, SHRM Foundation.
Watson, Towers K. (2010, August, 27). Creating sustainable rewards and talent management models: Results of the 2010 global talent management and reward studies. Vol 3, 126-201. Retrieved on September 13, 2010, from www.towerswatson.com/talent- management-rewards/key-findings.
Williamson, Lepak K. (2013). Human Resource Management. Oxford: Oxford University Press.